Context Engineering
Also called context management.
Context engineering is the practice of curating the full set of tokens a model sees at each step, including instructions, tools, retrieved data, memory, and conversation history, to maximize the chance of the desired behavior within a limited attention budget.
Description
The term gained currency in 2025 as agents ran for many steps and the main challenge shifted from wording a single prompt to deciding what information enters and leaves the context window over time, through techniques such as compaction, structured note-taking, and subagents.
Sources
- Anthropic (2025). Effective context engineering for AI agents.
Cite this entry
Protologue. (2026). Context Engineering. In Protologue: A Taxonomy of Prompting and LLM Techniques (v1.0.0, PTL-0072). https://protologue.com/t/context-engineering/
BibTeX
@misc{protologue_context_engineering,
title = {Context Engineering},
author = {{Protologue}},
year = {2026},
howpublished = {Protologue: A Taxonomy of Prompting and LLM Techniques, v1.0.0},
note = {Entry PTL-0072},
url = {https://protologue.com/t/context-engineering/}
}